Implementation Network for Sharing Population Information from Research Entities in East Africa (INSPIRE-EA)

应利用来自多个来源的高质量数据，就卫生政策和提供作出决定。联合国鼓励数据可查找、可访问、可互操作和可重复使用（FAIR），但非洲的许多数据尚未达到FAIR数据的标准。人口健康数据对于衡量包括全民健康覆盖在内的可持续发展目标（SDG）的许多指标非常重要。在大多数东非国家，卫生和人口哨点监测（HDSS）站点用于收集人口内部的卫生数据。ALPHA网络证明了如何利用艾滋病监测系统提供的艾滋病毒数据来显示艾滋病毒对人口的影响，以及艾滋病毒服务和政策（包括提供抗逆转录病毒治疗）对艾滋病毒感染者健康的影响。这个项目的总体目标是在东非建立共享来自研究实体的人口信息实施网络（INSPIRE）。这承认了在不同国家和不同环境下共享统一、公平数据的价值，并建立了产生这些数据的机制。INSPIRE网络将构建数据平台的关键组件。首先，我们将汇集通过HDSS收集原始数据的机构，并概述这样一个网络可能给HDSS带来的好处和支持。拟议的网络将以INDEPTH网络为模型，并使用南非的SAPRIN （www.saprin.mrc.ac.za）作为如何工作的例子。这一组成部分的目标是建立一种伙伴关系，将来自不同机构的人口健康数据转化为公平数据，从而能够进行高质量的分析，回答与政策有关的问题。第二个组成部分是建立公平数据的技术要求，并为产生数据奠定基础。在ALPHA网络工作的基础上，我们将采用自动化方法，让HDSS合作伙伴提取、转换和加载各自的HDSS数据到一个共同的数据库中。我们将通过行业标准数据文档保留数据的来源，这对FAIR数据很重要。该项目将开发和标准化描述非洲纵向人口健康数据的词汇，促进制定国际标准，以便研究人员能够理解和搜索这些数据。该项目将探索将人口健康数据与东非正在开发的电子健康记录（EHR）联系起来的方式。第三个组成部分将鼓励使用数据，以使平台可持续发展。该项目将确定数据的价值，改变对人口健康数据的态度，展示如何分析数据以回答重要的健康问题。纵向的人口健康数据虽然对了解卫生服务需求至关重要，但却被数字革命抛在了后面。迫切需要改变这种情况，并找到一种解决办法，提供统一的公平数据，以便在不同国家和不同健康状况之间进行比较。这个项目将建立发展和维持这样一个系统所需的伙伴关系，并将建立技术能力，以便能够建立一个公平的人口健康协调数据库。

Decisions on health policy and provision should be made using high quality data from multiple sources. The UN have encouraged data to be Findable, Accessible, Interoperable, and Reusable (FAIR) but much of the data in Africa has not reached the standards of FAIR data. Population data on health are important to measure many of the indicators for the Sustainable Development Goals (SDG), including the Universal Health Coverage (UHC). In most Eastern African countries, health and demographic sentinel surveillance (HDSS) sites are used to collect health data from within populations. The ALPHA network has demonstrated how HIV data from HDSS can be used to show how HIV affected the population, and the impact of HIV services and policies (including the delivery of anti-retroviral therapy) on the health of people living with HIV.The overall aim of this project is to create the Implementation Network for Sharing Population Information from Research Entities (INSPIRE) network in East Africa. This recognises the value of sharing harmonised, FAIR data across countries and across settings, and it sets up the mechanism by which these data can be produced. The INSPIRE network will build the key components for the data platform. Firstly we will bring together the institutions that collect primary data through HDSS, and to outline the benefits and support that such a network could bring to HDSS. The proposed network would be modelled on the INDEPTH network, and use SAPRIN in South Africa (www.saprin.mrc.ac.za) as an example of how it could work. The goal of this component is to establish a partnership which leverages population health data from different institutions into FAIR data that enables high quality analysis to answer policy relevant questions.The second component is to establish the technical requirements of FAIR data and to make the foundations to produce the data. Building on the work of ALPHA network, we will use automated methods for HDSS partners to extract, transform and load their own HDSS data into a common database. We will retain the provenance of the data through industry standard data documentation which is important for FAIR data.The project will develop and standardise the vocabulary to describe longitudinal population health data in Africa, contributing to international standards so that researchers can understand and search the data. The project will explore the way in which the population health data can be linked with the electronic health records (EHR), which are being developed in Eastern Africa.The third component will encourage the use of the data in order to make the platform sustainable. The project will identify the value of the data, and change the culture towards population health data, demonstrating how the data can be analysed to answer important health questions.Longitudinal, population data on health, while essential to understanding the demand for health services, has been left behind by the digital revolution. There is an urgent need to change this situation and find a solution which will provide harmonized FAIR data that can be compared across countries and across different health conditions. This project would establish the partnerships that are needed to develop and maintain such a system, and will set up the technical capacity to be able to set up a FAIR harmonised database for population health.